Field
Various systems and devices may benefit from cooperative resources management. For example, third and fourth generation wireless networks may benefit from a mechanism and apparatus to perform cooperative resource management, for example, for video downloads and for longer IP session flows.
Description of the Related Art
With the increasing popularity of smart phones and tablets, mobile data traffic may grow at a compound annual growth rate (CAGR) of 92 percent from 2010 to 2015, reaching 6.3 exabytes (1 exabyte is 1018 bytes) per month by 2015. Moreover, two-thirds of the world's mobile data traffic may be video by 2015.
Thus, operators, network vendors, and application service providers may need to come up with design and pricing models for handling controlled growth in internet traffic. This may especially be the case in mobile broadband, in which there is a constrained environment having scarce radio resources and user devices are constrained by battery and size limitations, for example.
Two factors that can be considered in mobile broadband with regard to data usage are signaling connection and data tonnage. The number of signaling connections that an application requires over the period of time impacts radio network scalability. Data tonnage occupies network resources for time needed for data to be transported and this demands additional capacity. Coordination between network and application may be useful in order to minimize data signaling and maximize the network scalability.
A large amount of the video data in a network may be the result of a small fraction of the http requests received from users. For example, 60% of video data volume may be generated by 2% of http requests received from the users, in a particular case.
The YouTube® service provided by Google, Inc. is an example of one popular video data service. YouTube® service currently uses a technique called progressive download, in which the video service is stored as a file at content delivery networks (CDNs) and delivered to the users upon requests. The client application can start playing video to the user after receiving a portion of the file content. The video can be delivered using hyper-text transfer protocol (HTTP) so that it works across many networks.
FIG. 1 illustrates a network trace of observed network traffic during the download of a video using HTTP. As shown in FIG. 1, the download time may be significantly shorter than the play time and a requested bit rate may be less than an available network bit rate. Thus, for example, a 360 second video clip may be downloaded in 115 seconds.
As the video is delivered over third generation and fourth generation (3G/4G) network systems, user terminals and the wireless network may have resource constrained environments that include such factors as battery, radio resources, and the like. However, conventional video protocols and delivery techniques do not consider these constraints as part of their design.
Moreover, lack of cooperation between application and wireless networks can lead to uneven load on a network, in terms of radio signaling and data wastage.
As mentioned above, FIG. 1 presents a trace that may be observed in a 3G/4G network, wherein the entire movie gets downloaded quickly. For video application, if data is made available early at the client, it may not have benefit to the client, because the client application will not consume the data immediately. The client application may only consume the data when video watching time has nearly approached. Additionally, if the user or subscriber of the client has a change of mind and prematurely terminates the video session, then most of the downloaded data may be wasted.
Thus, various side-effects may be observed in mobile network video delivery. Radio resource is a scare resource. Data wastage not only impacts user equipment (UE) battery life, but also imposes unnecessary traffic on the radio interface.
In another example, radio channels are limited. Because there is no idle time during video download in the example of FIG. 1, the number of concurrent sessions for video traffic may be limited, which may also limit network scalability. Likewise, there is no idle time observed in the network in FIG. 1. Once the video is requested by the user, the data keeps constantly flowing and results in no idle time.
In 3G/4G networks, Fast Dormancy, CELL PCH, and Continuous Packet Connectivity (CPC) aim to increase the efficiency of the radio resources. The assumption of these approaches is that application traffic is transactional, the traffic observed in the network either looks like a request/response or comes in short burst interval, and idle time is longer or comparable to active time. These approaches, however, cannot be applied to video traffic whether there is either no burst interval observed, or the burst interval has a long duration.
Additionally, video optimizers can be deployed in the network edge with a goal of throttling video traffic and minimizing bandwidth. These approaches do not scale well when more than 40% of the video traffic needs to be optimized. Moreover, in these approaches there is no coordination between radio signaling and throttling on the core network.